ACL 2025long0 citations

Towards Enhanced Immersion and Agency for LLM-based Interactive Drama

Hongqiu Wu, Weiqi Wu, Tianyang Xu, Jiameng Zhang, Hai Zhao

Abstract

LLM-based Interactive Drama is a novel AI-based dialogue scenario, where the user (i.e. the player) plays the role of a character in the story, has conversations with characters played by LLM agents, and experiences an unfolding story. This paper begins with understanding interactive drama from two aspects: Immersion—the player’s feeling of being present in the story—and Agency—the player’s ability to influence the story world. Both are crucial to creating an enjoyable interactive experience, while they have been underexplored in previous work. To enhance these two aspects, we first propose Playwriting-guided Generation, a novel method that helps LLMs craft dramatic stories with substantially improved structures and narrative quality. Additionally, we introduce Plot-based Reflection for LLM agents to refine their reactions to align with the player’s intentions. Our evaluation relies on human judgment to assess the gains of our methods in terms of immersion and agency.

BibTeX
@inproceedings{wu-etal-2025-towards-enhanced,
    title = "Towards Enhanced Immersion and Agency for {LLM}-based Interactive Drama",
    author = "Wu, Hongqiu  and
      Wu, Weiqi  and
      Xu, Tianyang  and
      Zhang, Jiameng  and
      Zhao, Hai",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.acl-long.546/",
    doi = "10.18653/v1/2025.acl-long.546",
    pages = "11166--11182",
    ISBN = "979-8-89176-251-0"
}
Towards Enhanced Immersion and Agency for LLM-based Interactive Drama · ACL 2025